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      <a class="article-title" href="/2017/05/20/distrute-in-action/">分布式服务化系统一致性的“最佳实干“</a>
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              一致性是一个抽象的、具有多重含义的计算机术语，在不同应用场景下，有不同的定义和含义。在传统的IT时代，一致性通常指强一致性，强一致性通常体现在你中有我、我中有你、浑然一体；而在互联网时代，一致性的含义远远超出了它原有的含义，在我们讨论互联网时代的一致性之前，我们先了解一下互联网时代的特点，互联网时代信息量巨大、需要计算能力巨大，不但对用户响应速度要求快，而且吞吐量指标也要向外扩展（既：水平伸缩），于是单节点的服务器无法满足需求，服务节点开始池化，想想那个经典的故事，一只筷子一折就断，一把筷子怎么都折不断，可见人多力量大的思想是多么的重要，但是人多也不一定能解决所有事情，还得进行有序、合理的分配任务，进行有效的管理，于是互联网时代谈论最多的话题就是拆分，拆分一般分为“水平拆分”和“垂直拆分”（大家不要对应到数据库或者缓存拆分，这里主要表达一种逻辑）。这里，“水平拆分”指的是同一个功能由于单机节点无法满足性能需求，需要扩展成为多节点，多个节点具有一致的功能，组成一个服务池，一个节点服务一部分的请求量，团结起来共同处理大规模高并发的请求量。“垂直拆分”指的是按照功能拆分，秉着“专业的人干专业的事儿”的原则，把一个复杂的功能拆分到多个单一的简单的元功能，不同的元功能组合在一起，和未拆分前完成的功能是一致的，由于每个元功能职责单一、功能简单，让维护和变更都变得更简单、安全，更易于产品版本的迭代，在这样的一个互联网的时代和环境，一致性指分布式服务化系统之间的弱一致性，包括应用系统一致性和数据一致性。
          
      
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              Spring Boot In Action
          
      
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              说起MySQL的查询优化，相信大家收藏了一堆奇淫技巧：不能使用`SELECT *`、不使用NULL字段、合理创建索引、为字段选择合适的数据类型..... 你是否真的理解这些优化技巧？是否理解其背后的工作原理？在实际场景下性能真有提升吗？我想未必。因而理解这些优化建议背后的原理就尤为重要，希望本文能让你重新审视这些优化建议，并在实际业务场景下合理的运用。
          
      
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              MySql 必知必会
          
      
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              Java8 In Action
          
      
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              Java8是2014年发布的，至今也已经有快三年的时间了，之前虽然有学习过，但是学的比较零散，不成系统，而且也没有覆盖到Java8所有的特性。 由于公司已经使用了JDK1.8，所以工作中能使用Java8的机会还是很多的，因此决定来系统地学习一下Java8的新特性，这是对我最近学习Java8的一些记录， 以备在有些细节记不太清的时候可以查询。
          
      
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      <a class="article-title" href="/2017/04/23/distribute-micro-service-1/">微服务业务开发三个难题－拆分、事务、查询（上）</a>
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              微服务架构变得越来越流行了。它是模块化的一种方法。它把一整块应用拆分成一个个服务。它让团队在开发大型复杂的应用时更快地交付出高质量的软件。团队成员们可以轻松地接受到新技术，因为他们可以使用最新且推荐的技术栈来实现各自的服务。微服务架构也通过让每个服务都被部署在最佳状态的硬件上而改善了应用的扩展性。
但微服务不是万能的。特别是在 领域模型、事务以及查询这几个地方，似乎总是不能适应拆分。或者说这几块也是微服务需要专门处理的地方，相对于过去的单体架构。
在这篇文章中，我会描述一种开发微服务的方法，这个方法可以解决这些问题。主要是通过领域模型设计，也就是DDD以及事件源（Event Sourcing）以及CQRS。让我们首先来看看开发人员在开发微服务的时候会遇到哪些问题吧。
          
      
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    <article id="post-distribute-micro-service-2" class="article article-type-post" itemscope itemprop="blogPost">
  
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              在本集中，我们将会向你介绍使用事件的时候遇到了一个新的问题，就是怎么样通过原子方式更新聚合和发布事件。然后会展示如何使用事件源来解决这个问题，**事件源**是一种以事件为中心的业务逻辑设计和持久化的方法。之后，我们会阐述微服务架构下的查询困难的问题。然后向你介绍一种称为**命令查询责任分离（CQRS）**的方法来实现可扩展和高性能的查询。
          
      
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              在复杂分布式系统中，往往需要对大量的数据和消息进行唯一标识。如在美团点评的金融、支付、餐饮、酒店、猫眼电影等产品的系统中，数据日渐增长，对数据分库分表后需要有一个唯一ID来标识一条数据或消息，数据库的自增ID显然不能满足需求；特别一点的如订单、骑手、优惠券也都需要有唯一ID做标识。此时一个能够生成全局唯一ID的系统是非常必要的。概括下来，那业务系统对ID号的要求有哪些呢？
          
      
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              阿里巴巴有2大核心的分布式技术，一个是OceanBase，另一个就是RocketMQ。在实际项目中已经领教过RocketMQ的强大，本人计划写一个RocketMQ实战系列，将涵盖RocketMQ的简介，环境搭建，初步使用、API详解、架构分析、管理员集群操作等知识。
          
      
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